Manager, Applied AI Engineering, Life Sciences
Leads and develops an applied AI engineering team delivering reliable, customer-facing agents, integrations, and scientific infrastructure for pharma and biotech organizations. The role combines hands-on engineering, partner ownership, cross-functional product influence, and responsible AI deployment in life sciences.
About the job
Responsibilities
- Hire, coach, and develop a team of Applied AI Engineers serving strategic life sciences partners.
- Own technical outcomes for pharma and biotech deployments from initial scoping through production.
- Review and contribute to prototypes, MCP integrations, agentic workflows, and Claude Code for Bio solutions.
- Guide development of deterministic tools, connectors, harnesses, and evaluations for reliable access to biological data and workflows.
- Partner with scientists, research institutions, go-to-market, product, research, and safety teams.
- Translate deployment insights into improvements for life sciences products and models.
- Establish responsible deployment practices in a sensitive, dual-use domain.
Requirements
- Experience leading or technically mentoring software or ML engineers, ideally in forward-deployed, solutions, or customer-facing engineering.
- Background in pharma, biotech, computational biology, bioinformatics, or clinical/regulatory affairs.
- Strong hands-on engineering background with production code.
- Experience delivering technical work directly with external customers or partners and communicating with technical experts and executives.
- Experience building on large language models or agents.
- Ability to learn unfamiliar technical domains quickly.
- High standards for reliability and reproducibility in scientific work.
- Experience building tooling, data infrastructure, evaluations, or agent harnesses for messy real-world data.
- Commitment to safe and beneficial AI deployment in sensitive domains.
- Bachelor's degree or equivalent combination of education, training, and experience.
Nice-to-haves
- Experience deploying LLM or agent systems in regulated or enterprise environments.
- Experience building MCP servers, developer tooling, or scientific computing pipelines.
- Experience scaling a customer-facing technical team during rapid growth.
Compensation and Benefits
- Annual salary: $320,000–$405,000 USD.
- Hybrid policy requiring staff to work from an office at least 25% of the time; some roles may require more.
- Visa sponsorship may be available.
Skills
Python, Machine Learning, LLMs, AI Agents, Mcp, Data Infrastructure, Bioinformatics, Computational Biology, Scientific Computing, Agent Evaluations, Production Engineering, Clinical Regulatory Affairs
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